CN110096762A - A kind of prediction of lathe rigging error and control method - Google Patents
A kind of prediction of lathe rigging error and control method Download PDFInfo
- Publication number
- CN110096762A CN110096762A CN201910288995.9A CN201910288995A CN110096762A CN 110096762 A CN110096762 A CN 110096762A CN 201910288995 A CN201910288995 A CN 201910288995A CN 110096762 A CN110096762 A CN 110096762A
- Authority
- CN
- China
- Prior art keywords
- error
- assembly
- deviation
- guide rail
- deformation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 29
- 230000005484 gravity Effects 0.000 claims abstract description 29
- 238000005096 rolling process Methods 0.000 claims abstract description 15
- 238000011217 control strategy Methods 0.000 claims abstract description 7
- 238000012546 transfer Methods 0.000 claims description 33
- 238000000429 assembly Methods 0.000 claims description 7
- 239000000284 extract Substances 0.000 abstract 1
- 238000009434 installation Methods 0.000 abstract 1
- 230000008569 process Effects 0.000 description 8
- 238000006073 displacement reaction Methods 0.000 description 7
- 239000011159 matrix material Substances 0.000 description 7
- 238000010586 diagram Methods 0.000 description 6
- 238000004458 analytical method Methods 0.000 description 5
- 238000012417 linear regression Methods 0.000 description 5
- 230000000694 effects Effects 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 238000004088 simulation Methods 0.000 description 3
- 238000013519 translation Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000003754 machining Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 229910000831 Steel Inorganic materials 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000002146 bilateral effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000000265 homogenisation Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000007790 scraping Methods 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 239000010959 steel Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/06—Power analysis or power optimisation
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Numerical Control (AREA)
Abstract
The invention discloses a kind of prediction of lathe rigging error and control methods, comprising the following steps: (1) based on Hertzian contact theory, establishes rolling guide error-workbench Error Propagation Model based on compatibility of deformation, and linearized；(2) it is directed to precise horizontal machining center, establishes finite element model by ABAQUS simulation software, extracts the gravity deformation result of each assembly step；(3) based on the assembly Error Propagation Model based on differential vector method, the complete machine error model for considering assembly deflections and guiding error is established；(4) it is directed to established complete machine error model, proposes corresponding rigging error adjustment, control strategy.The present invention has comprehensively considered influence of the rolling guide geometric error to error propagation, is more in line with objective installation situation；The changeability for considering gravity deformation, gradually analyzes deformation result, more accurately accomplishes gradually to predict and control end error.
Description
Technical Field
The invention relates to the field of assembly testing of numerical control machines, in particular to a method for predicting and controlling assembly errors of a machine tool by considering errors of a rolling guide rail and gravity deformation of a structural member.
Background
A high-speed, high-precision and high-reliability precision machining center becomes a development direction of modern equipment manufacturing industry [1], and a plurality of countries take development of precision numerical control machine tools as a primary task for development of high-end manufacturing industry. As an important numerical control machine tool, the precise horizontal machining center has a series of advantages of high automation degree, high machining efficiency and the like, and is widely applied to various fields of aerospace, aviation, precise die machining and the like.
There is no clear and effective guidance method for installing and adjusting the guide rail, which takes a lot of time in the assembly process, and technicians often neglect the effect of the geometric errors such as straightness and the like on the rolling joint surface, and the error transmission effect of the guide rail errors on the slide block and the moving part is considered. Meanwhile, the gravity deformation of parts in the assembly process has a great influence on assembly errors, an anti-deformation strategy is usually adopted for compensation in the assembly work of the machine tool at present, but the control quantity of the anti-deformation is not very accurate, the transfer effect of guide rail errors cannot be considered, and the functional relationship between the deformation deviation and the homogenization effect of the guide rail and the final assembly errors cannot be established.
Therefore, the traditional assembly process at present mainly depends on the experience of workers, scientific theoretical analysis and guide specifications are lacked, the assembly reliability is difficult to guarantee, and the assembly efficiency is low.
[1] Liujia, numerical control machine tool assembly failure rate modeling and control technology research [ D ]. Chongqing, university of Chongqing, Master academic paper, 2012.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides a method for predicting and controlling the assembly error of a machine tool by considering the error of a rolling guide rail and the gravity deformation of a structural member. By researching the assembly error transfer mechanism of the precision horizontal machining center and comprehensively considering the influence of guide rail errors and gravity deformation, an assembly error transfer model is established, an assembly error control and adjustment method is provided, a theoretical basis is provided for assembly error prediction control of the precision horizontal machining center, machine tool assembly personnel are scientifically guided to work, and the assembly precision and the assembly speed of the precision machine tool in China are greatly improved.
The purpose of the invention is realized by the following technical scheme:
a machine tool assembly error prediction and control method comprises the following steps:
(1) establishing a rolling guide rail error-workbench error transfer model based on deformation coordination based on a Hertz contact theory, and carrying out linearization;
(2) aiming at a precise horizontal machining center, establishing a finite element model by using ABAQUS simulation software, and extracting a gravity deformation result of each part in each assembly step;
(3) establishing a complete machine assembly error transfer model considering the gravity deformation of each component and the guide rail error on the basis of an assembly error model based on a differential vector method;
(4) and aiming at the established whole machine assembly error transfer model, providing corresponding assembly error adjustment and control strategies.
Further, the step (1) of establishing a rolling guide error-workbench error transfer model based on deformation coordination specifically comprises the following steps:
(101) establishing a coordinate system and defining errors at the gravity center of the moving part, on the table top and at the center of each sliding block;
(102) solving the deformation and contact force of the roller;
(103) establishing an error transfer model according to the stress balance;
(104) the error transfer model is linearized.
Further, the step (2) specifically comprises the following steps:
(201) setting an assembly step and selecting a spatial position;
(202) extracting the gravity deformation of the components in each assembly step;
(203) and calculating the straightness deviation and the angle deviation caused by gravity deformation.
Further, the step (3) specifically comprises the following steps:
(301) defining the assembling joint surfaces among the sub-assemblies as key product characteristics in an assembling error transfer model; defining the geometric deviation state of each key product characteristic;
(302) taking an assembly body formed by three parts as an example, deducing an assembly error transfer model;
(303) and establishing a complete machine assembly error transfer model of the horizontal machining center.
Further, the key product features in step (301) include: deviation of a bed column joint surface relative to a reference coordinate system, deviation of perpendicularity of an X-axis guide rail mounting plane of a column relative to a bed column joint surface, deviation of a slider surface of an X-axis guide rail, deviation of parallelism of a Y-axis guide rail mounting plane of a slide relative to a slide block joint surface of the slide, deviation of a slider surface of a Y-axis guide rail, deviation of parallelism of a main shaft end relative to a headstock slider joint surface, deviation of a Z-axis guide rail mounting plane of a bed relative to a reference coordinate system, deviation of a slider surface of a Z-axis guide rail and deviation of parallelism of a table upper surface relative to a table slider joint surface.
Further, the step (4) specifically comprises the following steps:
(401) measuring the assembled assembly body to obtain the deviation state of the assembled assembly body; under the deviation state of the existing assembly body, assuming that unassembled components have no errors, predicting the deviation state of the tail end of the whole machine to obtain a whole machine assembly error prediction result only considering the errors of the assembled components;
(402) measuring unassembled parts to obtain geometric deviation of the unassembled parts, and under the deviation state of the existing assembly body, predicting by using deviation measured values of the unassembled parts to replace actual errors of the unassembled parts to obtain a whole assembly error prediction result considering errors of all sub-assembly bodies;
(403) if only the deviation state that each item of the whole machine assembly error prediction result of the assembled component error exceeds the requirement is considered, adjusting the assembled components;
(404) if the whole machine assembly error prediction result obtained by only considering the errors of the assembled parts does not exceed the required deviation state, continuously judging whether the whole machine assembly error prediction result under the condition of considering the errors of all sub-assemblies exceeds the required deviation state or not, and if so, adjusting the unassembled parts; and (4) until the step (403) and the step (404) do not exceed the deviation requirement of the target characteristic, carrying out the next assembly until the assembly is completed.
Compared with the prior art, the technical scheme of the invention has the following beneficial effects: the influence of the geometric error of the rolling guide rail on the assembly error of the whole machine is comprehensively considered, and the established prediction model of the assembly error of the whole machine is more appropriate to the transmission process of the actual assembly error and more accords with the objective assembly condition; considering the variability of gravity deformation, extracting deformation results of each part in different assembly steps in the step (2), and calculating the gravity deformation in different assembly steps in the assembly error transfer model established in the step (3) to realize gradual prediction; and (4) by combining the precision machine tool assembly strategy provided in the step (4), errors of all parts can be gradually controlled in the assembly process, repeated scraping work is reduced, and the machine tool assembly work can be accurately and efficiently guided.
Drawings
FIG. 1 is a schematic diagram of a coordinate system of a workbench and a guide rail slider;
FIG. 2 is a schematic view of the assembly sequence of the machine tool;
FIG. 3 is a schematic diagram of the position of various components in a simulation;
FIG. 4 is a cloud of Y-direction displacements of the columns during each assembly step;
FIG. 5 is a cloud of Z-directional displacements of the bed during various assembly steps;
FIG. 6(a) is a Z-direction straightness error curve of the guide rail on the X-axis as a function of the assembly step;
FIG. 6(b) is a Y-direction straightness error curve of the guide rail on the X-axis as a function of the assembly step;
FIG. 7(a) is a Z-direction straightness error curve of the lower X-axis guide rail as a function of the assembly step;
FIG. 7(b) is a Y-direction straightness error curve of the lower X-axis guide rail as a function of the assembly step;
FIG. 8 is a graph of the rotational angle error about X of the axle guides as a function of the assembly step;
FIG. 9 is a schematic diagram of coordinate system and geometric deviation of key features of the bed and Z-axis guideway;
FIG. 10 is a schematic diagram of coordinate system and geometric deviation of key features of the columns and X-axis rails;
FIG. 11 is a schematic diagram of coordinate system and geometric deviation of key features of the sled and the Y-axis guide rails;
FIG. 12 is a schematic diagram of coordinate system and geometric deviation of key features of the headstock and the table;
FIG. 13 is a transfer process of geometric deviation and deformation deviation of a three-part assembly;
FIG. 14 is a flow chart of a machine tool assembly error control strategy.
Detailed Description
The invention is described in further detail below with reference to the figures and specific examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
1 rolling guide rail error-workbench error transfer model establishment
1.1 Hz contact theory
According to the hertzian contact theory, the relationship between contact deformation and contact pressure is:
in engineering applications, because the stress of the roller is complicated, the empirical formula (can be referred to as Zhupanska O I. contact protocol for elastic spheres, application of the hertz to non-small contact areas [ J ]. International Journal of engineering science 2011,49(7):576-588.) is mainly adopted:
wherein E is1，E2Is the modulus of elasticity of the roller and raceway surfaces; upsilon is1，υ2Is the poisson ratio of the roller and the raceway surface; r is the radius of the roller; l is the length of the roller.
The rollers and raceways are generally of steel material, their modulus of elasticity E andpoisson ratio v is the same, contact force Q is contact deformation deltanFunction of (c):
wherein,
for the rolling element, there are two contact points, where the deformation occurs simultaneously, belonging to bilateral deformation, so that the contact force of the rolling element ki can be obtained according to the empirical formula of hertzian contact theory:
wherein, FkiIs the contact force of the rolling elements in the k raceway on the i-th section, the direction of which depends on the contact angle. Δ dkiThe total deformation of the rollers, E and υ, are the modulus of elasticity and poisson ratio of the ball and raceway materials, respectively.
1.2 model for error transfer between slide and moving part
1.2.1 coordinate System establishment and definition of errors
For the dual-guide four-slider structure commonly used in the machine tool at present, firstly, a coordinate system is established at the gravity center of the moving part, on the table top and at the center of each slider, as shown in fig. 1. The center of gravity of the table being at a distance H from the mounting plane, i.e. the upper surface of the slide1The distance center of gravity of the table coordinate system is H2. The span of the guide rail is LvThe distance between two sliding blocks on the same guide rail is Lh. Suppose fourThe coordinate of the origin of the coordinate system of the slide block under the coordinate system of the moving part is xr,j,yr,j,zr,j](j＝1,2,3,4)。
Since the errors of the guide rails cause errors of the position and attitude of the moving parts, it is necessary to separately assume:
under the slider coordinate system, the guide rail error is:
Δg,j＝[δx,gj,δy,gj,θx,gj,θy,gj,θz,gj]T(7)
in the moving part coordinate system, the error of the moving part center is:
Δt＝[δx,t,δy,t,θx,t,θy,t,θz,t]T(8)
1.2.2 roller deformation and contact force solution
In the coordinate system of the moving part, the contact point A between the slide track k and the roller on any section i in the slide j without considering the deformation of the moving partr,jki＝[xr,jki,yr,jki,zr,jki]T, will move to A due to the influence of the errorr.j′＝[xr,jki′,yr,jki′,zr,jki′]T, namely:
similarly, in the coordinate system of the slide block, the guide rail error can cause the contact point A between the guide rail raceway k and the roller on any section i in the slide block jg＝[xg,jki,yg,jki,zg,jki]T will move to Ag′＝[xg,jki′,yg,jki′,zg,jki′]T, then:
unifying them under the coordinate system of moving part to obtain AgAnd Ar.j' the distance between changes is:
wherein Δ dpreFor pre-tensioning of the rolling elements, xr,jAnd yr,jIs the X and Y coordinates of the coordinate system origin of the j slide block under the coordinate system of the moving part.
From equations (5) - (6), the contact force of the roller can be found as:
1.2.3 stress balance analysis and error transfer model establishment
Under the coordinate system of the moving part, the contact resultant force and the contact resultant moment of all the rollers can be obtained, and the condition that the center of the moving part is subjected to an external force F is assumedx,t,Fy,tAnd the external force distance Mx,t,My,t,Mz,tAccording to the stress balance of the system, the following balance equation can be established:
from equation (13), the error Δ of the position of the four sliders is knowng,j＝[δx,gj,δy,gj,θx,gj,θy,gj,θz,gj]TUnder the conditions of (1), the five-dimensional error Δ t of the moving part [ δ ] can be obtained by the simultaneous equations (9) to (13)x,t,δy,t,θx,t,θy,t,θz,t]T。
The relationship between the error of the moving part and the respective errors of the four sliders is represented by the following equation (14):
Δt＝G(Δg,1,Δg,2,Δg,3,Δg,4) (14)
Δg,j＝[δx,gj,δy,gj,θx,gj,θy,gj,θz,gj]Terror of slider j, Δt＝[δx,t,δy,t,θx,t,θy,t,θz,t]TIs the error of the moving part.
1.2.4 error transfer model linearization
The model is a nonlinear model, and although the transfer relationship between the error of the four-slider and the error of the moving part can be described more accurately. However, the nonlinear relation is difficult to process in analysis and is not beneficial to predicting the assembly error of the whole machine, so that the method of multiple linear regression is adopted for linearization processing. The necessary variables were determined by performing significance analysis and then using Matlab to find the linear regression matrix $, i.e. ΔtAnd deltag,1,Δg,2,Δg,3,Δg,4Satisfies the following relationship:
then, a linear model of the error transfer between the moving part and the slide is established, knowing the error Δ of the position of the four slidesg,j＝[δx,gj,δy,gj,θx,gj,θy,gj,θz,gj]TUnder the condition (1), the five-dimensional error Delta of the moving part can be obtained by using the formula (15)t＝[δx,t,δy,t,θx,t,θy,t,θz,t]T。
2. Finite element simulation of complete machine assembly deformation
In the process of assembling the machine tool, the gravity action of each structural part can cause the deformation or displacement of the joint surface, and the assembly error of the whole machine tool is influenced. Since the assembly deformation cannot be obtained by means of measurement, the structure gravity deformation is extracted by the Abaqus simulation software.
2.1 Assembly step setting and spatial position selection
Because each structural member is assembled step by step, the gravity deformation result is different along with the change of the assembly steps, the gravity deformation result is required to be respectively obtained aiming at each assembly step, and the content of each assembly step is shown in fig. 2; meanwhile, as the static deformation shape state of the guide rail can be influenced to different degrees when each moving structural part is positioned at different spatial positions, 3 positions (as shown in fig. 3, three positions selected by each guide rail are respectively represented by 0,1 and 2) are selected at each guide rail shaft, so that simulation data of the three positions can be obtained, and then, the rest positions can be calculated by polynomial fitting, so that the deformation or displacement of any position can be obtained.
2.2 component deformation extraction at Each Assembly step
Taking the upper and lower guide rails of the upright column as an example, the deformation cloud pictures of the upright column in each assembly step are obtained as shown in fig. 4-5.
2.3 calculating the straightness and angle deviation caused by gravity
Through the displacement change result of finite element analysis, the guide rail straightness error and the angle error around the X axis caused by deformation in the assembling step can be separated. For the linearity error, the lowest point on the same guide rail is directly subtracted. For the error of the rotation angle around the X axis, the X axis guide rail is the difference value of the end point of the upper guide rail and the same end point of the lower guide rail, and then divided by the span of the guide rail, and the Y, Z axis guide rail is the difference value of the two end points of the same guide rail, and divided by the length of the guide rail.
Taking the column guide as an example, the straightness results after separation are shown in fig. 6(a) to 7(b), and the rotation angle of each shaft guide around the X axis is shown in fig. 8.
3. Complete machine error model established based on differential vector method
3.1 geometric deviation State definition of features
Since the variation of the overall assembly is mainly determined by the variation of the joint surfaces between the sub-assemblies, the assembly joint surface between the sub-assemblies is usually defined as a key product feature in the assembly error transfer model. Table 1 shows all the key product features defined, the specific locations of which are shown in fig. 9-12.
TABLE 1 symbols and meanings of geometric deviations of various junction surfaces
In three-dimensional space, each feature has six degrees of freedom in directions, namely, a translational degree of freedom in directions of three coordinate axes and a rotational degree of freedom around the three coordinate axes. Furthermore, the deviation state of the feature k with respect to its theoretical position and orientation can be represented by a 6 × 1 vector, namely:
[PkQk]T＝[ΔXk,ΔYk,ΔZk,Δθxk,Δθyk,Δθzk]T(16)
where k represents a feature number.
Considering the situation that form and position errors and gravity deformation exist simultaneously, for the deviation state of the characteristics, i is required to be introduced to represent an assembly step, namely:
when i-0 is in an unassembled state, and when i-k is in a state after the kth component is assembled, the definition is made.
First, since the geometric deviation of the features itself does not vary with the assembly step, it is defined as:
wherein, deltakAs a differential translation vector, ekThe rotation vector is differentiated.
The deviation due to the deformation of the feature by gravity will vary from assembly step to assembly step and is noted as:
wherein,in order to differentiate the translation vector(s),the rotation vector is differentiated.
3.2 derivation of general form of Assembly error transfer model, taking a three-part Assembly as an example
The differential vector method shows that:
r is a rotation matrix of 3x3, D is a translation matrix of 3x3, and D is a distance vector of the corresponding direction. The upper and lower corner marks represent the two coordinate systems where the transformation takes place.
As shown in fig. 13:
during the first assembly step, the face 1 is not yet deformed, only the geometric deviation:
during the assembly of second step, the deviation that the gravity deformation produced superposes with geometric deviation, and the deviation of face 1 is:
and the deviation of face 2 is:
in the same way, the deviation state of the characteristic k after the i-step assembly is popularized as follows:
and after the whole machine is assembled, namely n steps of assembly are completed, the deviation state of the characteristic k is as follows:
it should be noted that since the deformation deviation state is related to the assembly step, the intermediate state of the feature k is different from the state after the assembly is completed, namely:
when the n assembly sub-bodies of the assembly body are completely assembled, the states of all the characteristics are changed intoThe deviation of the feature n is then:
3.3 establishment of complete machine assembly error transfer model of precise horizontal machining center
Because the precise horizontal machining center is a closed-loop assembly body formed by assembling two open loops, the deviation of the main shaft and the deviation of the workbench are respectively obtained, and the assembly error transfer model of the whole machine can be obtained. The following is mainly to derive the deviation state of the main shaft as an example.
When the combined surface of the column of the lathe bed has geometric deviation, the deviation state is as follows:
according to equation (25), after the column and the X-axis guide rail are assembled, the deviation state of the surface of the X-axis guide rail slider is affected by both the self geometric deviation and the bed column junction surface and the X-axis guide rail mounting surface, so that the deviation state of the X-axis guide rail slider is:
the subscript sj denotes the sled shoe j; deltasj,εsjRespectively are the position error and the rotation angle error vector of the slide block of the slide plate.
The deviation state of the sliding plate can be deduced according to a linear regression error model between the sliding plate and the sliding block driving the sliding plate to move as follows:
wherein B issjAnd (j is 0,1..4) is a matrix of the sliding plate regression coefficient matrix corresponding to the sliding block j.
Similarly, considering the influence of the slide plate error and the spindle box slide block error on the spindle, the deviation state of the spindle is as follows:
wherein, BbjLinear regression coefficient matrix, delta, representing headstock slide jbj,εbjRespectively are displacement error and corner error vector of the main spindle box slide block.
Similarly, the deviation state of the workbench is as follows:
At,mj＝BtjW5,tj,At,nj＝BtjW6,tj,At,kj＝BtjWtj,tj
wherein, BtjLinear regression coefficient matrix, delta, representing the stage slide jtj,εtjRespectively are displacement error and rotation angle error vector of the worktable slide block.
The precision horizontal machining center is a closed-loop assembly body consisting of two assembly open loops, so that the deviation between the main shaft and the workbench is rotated to the same coordinate system, and the relative deviation between the workbench and the main shaft can be obtained as follows:
4. assembly error prediction and control strategy
The process-oriented assembly error control is a method for realizing that the final error meets the requirement by taking the error of each assembly step as a means. According to the established model, in the process of assembling the machine tool, the deviation and the error of the target feature can be predicted every time the machine tool is installed, and meanwhile, the influence degree of the assembled parts on the target feature can be analyzed, so that the following assembling error control strategy can be adopted.
The first step is as follows: measuring the assembled assembly body to obtain the deviation state [ P ]k,Qk]T(ii) a In the deviated state of the conventional assembly [ P ]k,Qk]TThen, assuming that the unassembled parts have no error, the state of the tail end deviation is predicted to obtain the prediction result of the whole assembly error only considering the errors of the assembled body
The second step is that: measuring the unassembled parts to obtain the geometric deviation deltak+1,εk+1]T. In the deviated state of the conventional assembly [ P ]k,Qk]TAnd then, replacing the actual error of the unassembled part with the deviation measured value of the unassembled part for prediction to obtain a complete machine assembly error prediction result considering the errors of all sub-assemblies
The third step: complete machine assembly error prediction result only considering assembled part errorsHas exceeded the required deviation stateThe assembled components must be adjusted.
The fourth step: the complete machine end error prediction result obtained by only considering the errors of the assembled partsNot surpassFor treatingThen the prediction result of the assembly error of the whole machine under the condition of considering all the errors of the sub-assembly bodies is continuously judgedWhether or not to exceedIf the number of the parts exceeds the preset value, the parts which are not assembled are adjusted. Can be predicted by analyzing two kinds of prediction results (And) And (4) judging error sources and whether the error sources are greatly influenced by the assembled components or the unassembled components, adjusting the error sources with large influence, and carrying out next assembly until the third step and the fourth step do not exceed the deviation requirement of the target characteristics until the assembly is finished.
The flow of the above-described assembly error control strategy is shown in FIG. 14 below.
The present invention is not limited to the above-described embodiments. The foregoing description of the specific embodiments is intended to describe and illustrate the technical solutions of the present invention, and the above specific embodiments are merely illustrative and not restrictive. Those skilled in the art can make many changes and modifications to the invention without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (6)
1. A machine tool assembly error prediction and control method is characterized by comprising the following steps:
(1) establishing a rolling guide rail error-workbench error transfer model based on deformation coordination based on a Hertz contact theory, and carrying out linearization;
(2) aiming at a precise horizontal machining center, establishing a finite element model by using ABAQUS simulation software, and extracting a gravity deformation result of each part in each assembly step;
(3) establishing a complete machine assembly error transfer model considering the gravity deformation of each component and the guide rail error on the basis of an assembly error model based on a differential vector method;
(4) and aiming at the established whole machine assembly error transfer model, providing corresponding assembly error adjustment and control strategies.
2. The machine tool assembly error prediction and control method according to claim 1, wherein the step (1) of establishing the rolling guide error-workbench error transfer model based on deformation coordination specifically comprises the following steps:
(101) establishing a coordinate system and defining errors at the gravity center of the moving part, on the table top and at the center of each sliding block;
(102) solving the deformation and contact force of the roller;
(103) establishing an error transfer model according to the stress balance;
(104) the error transfer model is linearized.
3. The machine tool assembly error prediction and control method of claim 1, wherein the step (2) comprises the following steps:
(201) setting an assembly step and selecting a spatial position;
(202) extracting the gravity deformation of the components in each assembly step;
(203) and calculating the straightness deviation and the angle deviation caused by gravity deformation.
4. The machine tool assembly error prediction and control method of claim 1, wherein the step (3) comprises the following steps:
(301) defining the assembling joint surfaces among the sub-assemblies as key product characteristics in an assembling error transfer model; defining the geometric deviation state of each key product characteristic;
(302) taking an assembly body formed by three parts as an example, deducing an assembly error transfer model;
(303) and establishing a complete machine assembly error transfer model of the horizontal machining center.
5. The machine tool assembly error prediction and control method of claim 4, wherein the key product features of step (301) comprise: deviation of a bed column joint surface relative to a reference coordinate system, deviation of perpendicularity of an X-axis guide rail mounting plane of a column relative to a bed column joint surface, deviation of a slider surface of an X-axis guide rail, deviation of parallelism of a Y-axis guide rail mounting plane of a slide relative to a slide block joint surface of the slide, deviation of a slider surface of a Y-axis guide rail, deviation of parallelism of a main shaft end relative to a headstock slider joint surface, deviation of a Z-axis guide rail mounting plane of a bed relative to a reference coordinate system, deviation of a slider surface of a Z-axis guide rail and deviation of parallelism of a table upper surface relative to a table slider joint surface.
6. The machine tool assembly error prediction and control method according to claim 1, wherein the step (4) specifically comprises the following steps:
(401) measuring the assembled assembly body to obtain the deviation state of the assembled assembly body; under the deviation state of the existing assembly body, assuming that unassembled components have no errors, predicting the deviation state of the tail end of the whole machine to obtain a whole machine assembly error prediction result only considering the errors of the assembled components;
(402) measuring unassembled parts to obtain geometric deviation of the unassembled parts, and under the deviation state of the existing assembly body, predicting by using deviation measured values of the unassembled parts to replace actual errors of the unassembled parts to obtain a whole assembly error prediction result considering errors of all sub-assembly bodies;
(403) if only the deviation state that each item of the whole machine assembly error prediction result of the assembled component error exceeds the requirement is considered, adjusting the assembled components;
(404) if the whole machine assembly error prediction result obtained by only considering the errors of the assembled parts does not exceed the required deviation state, continuously judging whether the whole machine assembly error prediction result under the condition of considering the errors of all sub-assemblies exceeds the required deviation state or not, and if so, adjusting the unassembled parts; and (4) until the step (403) and the step (404) do not exceed the deviation requirement of the target characteristic, carrying out the next assembly until the assembly is completed.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910288995.9A CN110096762B (en) | 2019-04-11 | 2019-04-11 | Machine tool assembly error prediction and control method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910288995.9A CN110096762B (en) | 2019-04-11 | 2019-04-11 | Machine tool assembly error prediction and control method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110096762A true CN110096762A (en) | 2019-08-06 |
| CN110096762B CN110096762B (en) | 2023-06-30 |
Family
ID=67444685
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910288995.9A Active CN110096762B (en) | 2019-04-11 | 2019-04-11 | Machine tool assembly error prediction and control method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110096762B (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110853134A (en) * | 2019-10-25 | 2020-02-28 | 西安交通大学 | Method for calculating contact state of assembly matching surface containing geometric errors |
| CN111015246A (en) * | 2019-12-19 | 2020-04-17 | 西安交通大学 | Method for determining assembly parallelism of ball linear guide rail based on dynamic characteristics of feeding system of numerical control machine tool |
| CN112735483A (en) * | 2020-11-17 | 2021-04-30 | 北京理工大学 | Method for improving assembly performance by improving modeling by utilizing design errors |
| CN113496064A (en) * | 2021-09-07 | 2021-10-12 | 北京精雕科技集团有限公司 | Compensation adjustment method for straightness of numerical control machine tool |
| CN114265365A (en) * | 2021-12-21 | 2022-04-01 | 重庆大学 | Gear grinding machine thermal error dynamic modeling and compensation method based on online measurement |
| CN116384257A (en) * | 2023-05-29 | 2023-07-04 | 浙江大学 | Method for predicting assembly errors and optimizing tolerance of air separation integral cold box |
| CN116611166A (en) * | 2023-05-23 | 2023-08-18 | 南京航空航天大学 | Aircraft component multi-level assembly deviation analysis method considering initial error |
| CN117786886A (en) * | 2023-12-28 | 2024-03-29 | 上海交通大学 | Parallel structure deviation transfer analysis method considering tenon-mortise contact deformation |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103366050A (en) * | 2013-06-25 | 2013-10-23 | 华中科技大学 | High-speed electric spindle power-heat coupling modeling method |
| CN104102774A (en) * | 2014-07-08 | 2014-10-15 | 西安交通大学 | Method for designing linearity of mounting surface for rolling linear guide of precision machine tool |
| CN104217080A (en) * | 2014-09-03 | 2014-12-17 | 西安交通大学 | Kinematic error prediction model building and prediction method for rolling line feed system |
| CN105573248A (en) * | 2016-01-13 | 2016-05-11 | 南京航空航天大学 | Flexible member assembling dimensional deviation control method based on multi-station assembly jig compensation |
| CN107247841A (en) * | 2017-06-09 | 2017-10-13 | 北京理工大学 | A kind of rectangular spline Contact Dynamics emulation mode based on assembly features information |
| CN108763152A (en) * | 2018-04-27 | 2018-11-06 | 西安交通大学 | A kind of precision machine tool computer aided tolerance analysis method based on stl file |
| CN108803497A (en) * | 2018-05-24 | 2018-11-13 | 天津大学 | A kind of modeling method of guiding error-moving component position and attitude error mapping model |
-
2019
- 2019-04-11 CN CN201910288995.9A patent/CN110096762B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103366050A (en) * | 2013-06-25 | 2013-10-23 | 华中科技大学 | High-speed electric spindle power-heat coupling modeling method |
| CN104102774A (en) * | 2014-07-08 | 2014-10-15 | 西安交通大学 | Method for designing linearity of mounting surface for rolling linear guide of precision machine tool |
| CN104217080A (en) * | 2014-09-03 | 2014-12-17 | 西安交通大学 | Kinematic error prediction model building and prediction method for rolling line feed system |
| CN105573248A (en) * | 2016-01-13 | 2016-05-11 | 南京航空航天大学 | Flexible member assembling dimensional deviation control method based on multi-station assembly jig compensation |
| CN107247841A (en) * | 2017-06-09 | 2017-10-13 | 北京理工大学 | A kind of rectangular spline Contact Dynamics emulation mode based on assembly features information |
| CN108763152A (en) * | 2018-04-27 | 2018-11-06 | 西安交通大学 | A kind of precision machine tool computer aided tolerance analysis method based on stl file |
| CN108803497A (en) * | 2018-05-24 | 2018-11-13 | 天津大学 | A kind of modeling method of guiding error-moving component position and attitude error mapping model |
Non-Patent Citations (2)
| Title |
|---|
| GAIYUN HE 等: ""Simulation and analysis for accuracy predication and adjustment for machine tool assembly process"", 《ADVANCES IN MECHANICAL ENGINEERING》 * |
| 李素乾: ""精密卧式加工中心装配误差控制关键技术研究"", 《中国优秀硕士学位论文全文数据库 工程科技Ⅰ辑》 * |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110853134A (en) * | 2019-10-25 | 2020-02-28 | 西安交通大学 | Method for calculating contact state of assembly matching surface containing geometric errors |
| CN111015246A (en) * | 2019-12-19 | 2020-04-17 | 西安交通大学 | Method for determining assembly parallelism of ball linear guide rail based on dynamic characteristics of feeding system of numerical control machine tool |
| CN112735483A (en) * | 2020-11-17 | 2021-04-30 | 北京理工大学 | Method for improving assembly performance by improving modeling by utilizing design errors |
| CN113496064A (en) * | 2021-09-07 | 2021-10-12 | 北京精雕科技集团有限公司 | Compensation adjustment method for straightness of numerical control machine tool |
| CN113496064B (en) * | 2021-09-07 | 2021-11-30 | 北京精雕科技集团有限公司 | Compensation adjustment method for straightness of numerical control machine tool |
| CN114265365A (en) * | 2021-12-21 | 2022-04-01 | 重庆大学 | Gear grinding machine thermal error dynamic modeling and compensation method based on online measurement |
| CN114265365B (en) * | 2021-12-21 | 2024-05-28 | 重庆大学 | Online measurement-based dynamic modeling and compensation method for thermal error of gear grinding machine |
| CN116611166B (en) * | 2023-05-23 | 2024-03-12 | 南京航空航天大学 | Aircraft component multi-level assembly deviation analysis method considering initial error |
| CN116611166A (en) * | 2023-05-23 | 2023-08-18 | 南京航空航天大学 | Aircraft component multi-level assembly deviation analysis method considering initial error |
| CN116384257B (en) * | 2023-05-29 | 2023-09-29 | 浙江大学 | Method for predicting assembly errors and optimizing tolerance of air separation integral cold box |
| CN116384257A (en) * | 2023-05-29 | 2023-07-04 | 浙江大学 | Method for predicting assembly errors and optimizing tolerance of air separation integral cold box |
| CN117786886A (en) * | 2023-12-28 | 2024-03-29 | 上海交通大学 | Parallel structure deviation transfer analysis method considering tenon-mortise contact deformation |
| CN117786886B (en) * | 2023-12-28 | 2024-09-03 | 上海交通大学 | Parallel structure deviation transfer analysis method considering tenon-mortise contact deformation |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110096762B (en) | 2023-06-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110096762A (en) | A kind of prediction of lathe rigging error and control method | |
| Ibaraki et al. | Machining tests to identify kinematic errors on five-axis machine tools | |
| CN108445839B (en) | Machine tool precision sensitivity analysis method based on error increment | |
| CN101493683A (en) | Method for implementing numerical control finish machining for large component of aeroplane based on digitalization error compensation template | |
| CN112008492A (en) | Method for identifying perpendicularity error of translational shaft of gantry numerical control machine tool | |
| TWI772717B (en) | Positioning machine, device for mechanical correction of mounting surface of axis guide component of positioning machine, and method for mechanical correction of geometric motion errors of positioning machine | |
| Ma et al. | Assembly errors analysis of linear axis of CNC machine tool considering component deformation | |
| Li et al. | Compensation of dynamic mechanical tracking errors in ball screw drives | |
| Liu et al. | Dynamics analysis on the MDOF model of ball screw feed system considering the assembly error of guide rails | |
| Putilova et al. | Loading of the manufacturing systems elements in the process of unsteady mode cutting and the models of their arrangement deviations | |
| CN113985812A (en) | Machining error forecasting method for multi-axis numerical control machine tool | |
| Fu et al. | Review on structure-based errors of parallel kinematic machines in comparison with traditional NC machines | |
| CN104965958B (en) | A kind of error compensation control method of stacking-type workbench | |
| Tianyi et al. | Error modeling and compensating of a novel 6-DOF aeroengine rotor docking equipment | |
| CN108803497A (en) | A kind of modeling method of guiding error-moving component position and attitude error mapping model | |
| Guo et al. | The modeling and prediction of gravity deformation in precision machine tool assembly | |
| CN110110381B (en) | Thermal error sensing method for horizontal machining center process information | |
| CN106020115A (en) | Influence analytical method for identifying load error of static-pressure rotary table and analyzing influence of load error on machining error of machine tool | |
| Kwintarini et al. | Modeling of Geometric Error in Linear Guide Way to Improved the vertical three-axis CNC Milling machine’s accuracy | |
| Kwintarini et al. | Mathematical approach for geometric error modeling of three axis CNC vertical milling machine | |
| Ramos et al. | Application of the Denavit-Hartenberg method to estimate the positioning errors of an automated XYZ cartesian table | |
| KURIC et al. | MACHINE TOOL ERRORS AND ITS SIMULATION ON EXPERIMENTAL DEVICE. | |
| Teng et al. | A Summary on Stiffness Analysis Method of Machine Tools | |
| Ghionea et al. | Applicative CAD/CAM methodology for parameterization the rolling surface of railway wheels | |
| CN109521729A (en) | A kind of three axis numerically controlled machine can compensate for and not can compensate for geometric error separation method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |